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<front>
<journal-meta>
<journal-id>0301-603X</journal-id>
<journal-title><![CDATA[South African Journal of Agricultural Extension ]]></journal-title>
<abbrev-journal-title><![CDATA[S Afr. Jnl. Agric. Ext.]]></abbrev-journal-title>
<issn>0301-603X</issn>
<publisher>
<publisher-name><![CDATA[South African Society of Agricultural Extension (SASAE)]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S0301-603X2011000200003</article-id>
<title-group>
<article-title xml:lang="en"><![CDATA[Effectiveness of the farmer-to-farmer extension model in increasing technology uptake in Masaka and Tororo Districts of Uganda]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Ssemakula]]></surname>
<given-names><![CDATA[E.]]></given-names>
</name>
<xref ref-type="aff" rid="A01"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Mutimba]]></surname>
<given-names><![CDATA[J. K.]]></given-names>
</name>
<xref ref-type="aff" rid="A02"/>
</contrib>
</contrib-group>
<aff id="A01">
<institution><![CDATA[,Bishop Stuart University Faculty of Applied Sciences ]]></institution>
<addr-line><![CDATA[Mbarara ]]></addr-line>
<country>Uganda</country>
</aff>
<aff id="A02">
<institution><![CDATA[,Winrock-SAFE  ]]></institution>
<addr-line><![CDATA[Addis Ababa ]]></addr-line>
<country>Ethiopia</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>00</month>
<year>2011</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>00</month>
<year>2011</year>
</pub-date>
<volume>39</volume>
<numero>2</numero>
<fpage>30</fpage>
<lpage>46</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.za/scielo.php?script=sci_arttext&amp;pid=S0301-603X2011000200003&amp;lng=en&amp;nrm=iso&amp;tlng=en"></self-uri><self-uri xlink:href="http://www.scielo.org.za/scielo.php?script=sci_abstract&amp;pid=S0301-603X2011000200003&amp;lng=en&amp;nrm=iso&amp;tlng=en"></self-uri><self-uri xlink:href="http://www.scielo.org.za/scielo.php?script=sci_pdf&amp;pid=S0301-603X2011000200003&amp;lng=en&amp;nrm=iso&amp;tlng=en"></self-uri><abstract abstract-type="short" xml:lang="en"><p><![CDATA[An effective extension model focuses strongly on the dissemination and facilitation of the adoption of recommended technologies and practices to achieve its objectives. The farmer-to-farmer extension model has proved a success in Latin America (Kruger, 1995; Simpson and Owens, 2002; Hellin, Rodriguez and Coello, 2002), the Far East (Farrington and Martin, 1993) and a number of African countries in sub-Saharan Africa (Muok, Kimondo and Atshusi, 2001). In recent years, the model has been introduced in Uganda following the perceived ineffectiveness of the public extension models. However, the success of the new model has not been tested or established. This study was, therefore designed to provide evidence of its performance. The objectives of the study, which was conducted in two districts of Uganda (Masaka and Tororo), were to: a) identify the key players in the farmer-to-farmer extension approach; b) explain the nature and characteristics of the major players; c) examine the roles played by key players in the communities; d) determine appropriate communication channels in the communities; and e) identify the determinants of the effectiveness of the farmer-to-farmer extension model The effectiveness of the farmer-to-farmer extension approach was measured by: i) increased technology uptake; ii) increased production; iii) increased food availability; iv) the multiplier effect in information-sharing; and v) increased sales of commodities. The results were compared to those in areas where the farmer-to-farmer approach was not applied but with all other conditions remaining the same. The effectiveness of the model was found to depend on facilitators in terms of: Faculty of Applied Sciences Bishop Stuart University P.O. Box 9, Mbarara, Uganda Winrock-SAFE, P.O. Box 24135, Code 1000, Addis Ababa, Ethiopia a) their socio-economic closeness to the beneficiaries; b) their multiple community roles which boosted communication networks; c) their role in enhanced information flow among individuals of similar social status; d) better interaction and information-sharing among beneficiaries; e) their being community-based they devoted more time to their fellow beneficiaries; f) their use of demonstration facilities for experiential learning. The model can be applicable in a wide range of development fields where beneficiaries assume roles of development facilitators in their own communities]]></p></abstract>
<kwd-group>
<kwd lng="en"><![CDATA[Farmer-to-farmer extension]]></kwd>
<kwd lng="en"><![CDATA[community facilitators]]></kwd>
<kwd lng="en"><![CDATA[information flow]]></kwd>
<kwd lng="en"><![CDATA[effectiveness]]></kwd>
</kwd-group>
</article-meta>
</front><body><![CDATA[ <p><font face="Verdana, Arial, Helvetica, sans-serif" size="4"><b><a name="top"></a>Effectiveness    of the farmer-to-farmer extension model in increasing technology uptake in Masaka    and Tororo Districts of Uganda</b></font></p>     <p>&nbsp;</p>     <p>&nbsp;</p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2"><b>E. Ssemakula<sup>I</sup>;    J. K. Mutimba<sup>II</sup></b></font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2"><sup>I</sup>Faculty    of Applied Sciences Bishop Stuart University P.O. Box 9, Mbarara, Uganda    <br>   <sup>II</sup>Winrock-SAFE, P.O. Box 24135, Code 1000, Addis Ababa, Ethiopia</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2"><a href="#back">Corresponding    author</a></font></p>     <p>&nbsp;</p>     <p>&nbsp;</p> <hr size="1" noshade>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2"><b>ABSTRACT</b></font></p>     ]]></body>
<body><![CDATA[<p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">An effective extension    model focuses strongly on the dissemination and facilitation of the adoption    of recommended technologies and practices to achieve its objectives. The farmer-to-farmer    extension model has proved a success in Latin America (Kruger, 1995; Simpson    and Owens, 2002; Hellin, Rodriguez and Coello, 2002), the Far East (Farrington    and Martin, 1993) and a number of African countries in sub-Saharan Africa (Muok,    Kimondo and Atshusi, 2001). In recent years, the model has been introduced in    Uganda following the perceived ineffectiveness of the public extension models.    <br>   However, the success of the new model has not been tested or established. This    study was, therefore designed to provide evidence of its performance.    <br>   The objectives of the study, which was conducted in two districts of Uganda    (Masaka and Tororo), were to:    <br>   a)&nbsp;identify the key players in the farmer-to-farmer extension approach;    <br>   b)&nbsp;explain the nature and characteristics of the major players;    <br>   c)&nbsp;examine the roles played by key players in the communities;    <br>   d)&nbsp;determine appropriate communication channels in the communities; and    <br>   e)&nbsp;identify the determinants of the effectiveness of the farmer-to-farmer    extension model    <br>   The effectiveness of the farmer-to-farmer extension approach was measured by:    <br>   i)&nbsp;increased technology uptake;    ]]></body>
<body><![CDATA[<br>   ii)&nbsp;increased production;    <br>   iii)&nbsp;increased food availability;    <br>   iv)&nbsp;the multiplier effect in information-sharing; and    <br>   v)&nbsp;increased sales of commodities.    <br>   The results were compared to those in areas where the farmer-to-farmer approach    was not applied but with all other conditions remaining the same.    <br>   The effectiveness of the model was found to depend on facilitators in terms    of:    <br>   Faculty of Applied Sciences Bishop Stuart University P.O. Box 9, Mbarara, Uganda    Winrock-SAFE, P.O. Box 24135, Code 1000, Addis Ababa, Ethiopia    <br>   a)&nbsp;their socio-economic closeness to the beneficiaries;    <br>   b)&nbsp;their multiple community roles which boosted communication networks;    <br>   c)&nbsp;their role in enhanced information flow among individuals of similar    social status;    ]]></body>
<body><![CDATA[<br>   d)&nbsp;better interaction and information-sharing among beneficiaries;    <br>   e)&nbsp;their being community-based they devoted more time to their fellow beneficiaries;    <br>   f)&nbsp;their use of demonstration facilities for experiential learning.    <br>   The model can be applicable in a wide range of development fields where beneficiaries    assume roles of development facilitators in their own communities</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2"><b>Key words:</b>    Farmer-to-farmer extension, community facilitators, information flow, effectiveness.</font></p> <hr size="1" noshade>     <p>&nbsp;</p>     <p>&nbsp;</p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="3"><b>1. INTRODUCTION</b></font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">An extension model    is the general statement of the intellectual, infrastructural and political    framework within which the extension service will be performed (Donkoh, Albert,    Hesse, &amp; Amoakoh, 1999).</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">An important way    of grouping extension models is, among other criteria, according to the degree    of participation by the beneficiaries. Three broad strategies can be distinguished,    namely</font></p>     ]]></body>
<body><![CDATA[<p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">i)&nbsp;the transfer    of technology or the transfer of advice, information, knowledge and skills to    farmers. This strategy has been widely applied by the traditional extension    services and is characterised by bureaucratic management structures;</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">ii)&nbsp;advisory    services, which comprise a cadre of experts whom farmers use as a source of    advice in relation to specific problems they have identified. This strategy    features prominently in the Uganda National Agricultural Advisory Services (NAADS)    where specialised advice is given on selected enterprises.</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">iii)&nbsp;the participatory    approach, where farmers or other beneficiaries identify their own problems and    develop their own solutions. This strategy is widely applied by non-government    organisations (NGOs) and is a characteristic of the farmer-to-farmer extension    service. In this model beneficiaries are fully involved in identifying problems,    suggesting solutions and disseminating technologies and practices. (Nalukwago    2004).</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2"><b>1.1 The philosophical    basis and assumptions of the strategies</b></font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">The first strategy    was based on the philosophy that the information to develop and the assumption    that technologies were sourced from research and that it was the duty of the    public extension agent to transfer knowledge about the technologies to the farmers.    Farmers were viewed as objects of technology and that they played no part in    generating and/or disseminating it. The public extension services providers    were generally non practitioners and were not closely related to their clients    in the communities. In public extension, it is not easy to ensure both technical    and financial accountability.</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">The second strategy    was based on the assumption that farmers had specific technology needs which    required specialised expertise. The experts were to be hired according to the    special needs groups depending on the enterprises selected and the experts would    offer advisory services. Advisory services are offered by contracted extension    services providers over a limited time. This strategy does not ensure continued    contact of experts with the beneficiaries since contract for services are for    short periods.</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">The third strategy    was based on the assumption that an extension service is a participatory process,    whereby the beneficiaries are involved in technology generation and dissemination.    The services providers are located in the communities and continuously interact    with the beneficiaries about the production value chain. The approach philosophically    believes in starting small, utilise all available resources to the maximum and    always innovate. The process operates on the basis of agroecology, where organic    farming is encouraged as opposed to agro-industrial process, where industrial    chemicals are widely used. The third strategy ensures accountability and commitment    of the extension services providers.</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2"><b>1.2</b>&nbsp;<b>Determinants    of effectiveness of the extension service</b></font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">For any extension    model to be deemed effective it should be able to improve production and productivity    (Rivera and Carry, 1998), and at the same time be readily available and accessible    (Chambers, 1990). Past extension services models lacked both these vital requirements    and thus proved ineffective. The farmer-to-farmer extension approach is meant    to address these weaknesses.</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2"><b>1.3</b>&nbsp;<b>Attributes    of an Effective Extension Model</b></font></p>     ]]></body>
<body><![CDATA[<blockquote>        <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">A number of attributes      combine to constitute an effective extension model and include:</font></p>       <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">a)&nbsp;A clear      and inclusive philosophy</font></p>       <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">b)&nbsp;Knowledge      and commitment of the extension providers</font></p>       <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">c)&nbsp;Social      proximity of extension services providers and beneficiaries</font></p>       <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">d)&nbsp;Involvement      of the beneficiaries in the process of technology generation and dissemination</font></p>       <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">e)&nbsp;Availability      of the services</font></p>       <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">f)&nbsp;Improving      productivity of enterprises</font></p>       <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">g)&nbsp;Presence      of supportive policies, institutions, programmes and related enabling processes</font></p> </blockquote>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">A clear and inclusive    philosophy of the model will address both the technical content of the technology    plus the management processes and mechanisms of implementation. It should aim    at high yields or production and quality plus leadership and organization of    beneficiaries in order to maximise outputs and outcomes. It would also address    the entire value chain of the enterprise. The public extension services generally    aim at addressing the efficacy of technology and do little to address the supportive    processes.</font></p>     ]]></body>
<body><![CDATA[<p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">Knowledge and commitment    of the extension providers is the key to the effectiveness of the model. Knowledge    of the technical content in addition to practical application are vital for    ensuring the effectiveness of the model. The public extension services providers    are highly trained in theoretical aspects but generally lack practical experiences    and commitment to the service. The farmer-to-farmer extension providers are    not highly technically trained but have practical experiences being practising    farmers and are committed to serving their peers.</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">Social proximity,    which is sharing similar socio-economic characteristics and behaviour, is the    key to information sharing. Public extension services models are managed by    agents of different socio-economic backgrounds from those of the beneficiaries    and thus find it difficult to interact with them.</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">Involvement of    the beneficiaries in the process of technology generation and dissemination    enhances the effectiveness of the extension model since it builds ownership    of the intervention. Public extension services involve beneficiaries at the    levels technology transfer only but not in generation and dissemination. However,    the farmer-to-farmer extension involves beneficiaries in all relevant processes.</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">Availability of    the services to beneficiaries at all times contributes to the effectiveness    of the model. Public extension services are normally extended at the beginning    of the planting seasons and at limited periods. The farmer-to-farmer extension    is however available all the time.</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">Improving productivity    of enterprises is the utmost aim of any extension model. However, increased    productivity does not depend on the efficacy of the technology as is generally    viewed. It will in addition depend on the management processes of the technology    throughout the entire value chain. The farmer-to-farmer extension model covers    the entire needs of the value chain unlike the public extension model, which    only covers parts.</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">Finally, effectiveness    of any extension model will depend on the supportive policies covering fiscal    and political dimensions. It will also depend on the effective operation of    line institutions such as government ministries and programmes plus sportive    implementation processes.</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">Referring to the    farmer-to-farmer extension approach, Kruger (1995) explained that it was effective    as it addressed the limiting factors that inhibit peasants' food production,    including soil, water and organic matter. Clearly for the approach to be deemed    effective must achieve the set objectives. Generally, the set objectives include    increased production and eradication of poverty (Rivera &amp; Amanor, 1991).    The major reason why new approaches are being sought was due to failure of the    existing or past approaches to achieve the intended objectives (Swanson &amp;    Samy, 2002). For an approach to be effective it should also have a clear and    inclusive working philosophy. The failure of the progressive farmers' approach    and most approaches modelled on the training-and-visit approach was blamed on    the fact that it emphasised only the hardcore technical philosophy in disregard    of other aspects necessary for effective dissemination of technologies, such    as communication processes, leadership and institutional organisation (Nagel,    1997).</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">The wide scope    of the farmer-to-farmer extension model was also pointed out by Kruger (1995)    when explaining the nature and operation of the farmer-to-farmer extension approach.    He emphasized that it was an approach to sustainable development resting firmly    on the principles of respect for traditional knowledge from the existing farmers;    it also emphasised farmer experimentation, sharing of knowledge and innovations.    Similarly, Duveskog, Mburu &amp; Critchley (2002) asserted that there were indications    of a higher level of adoption when new technology options were introduced by    fellow farmers than by external agents. Often when technologies were demonstrated    in the communities by external agents, the focus was on the technology mainly,    with scanty attention being paid to other aspects, such as finding a market    for the produce or controlling diseases.</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">But if the farmer    introduces the technology he/she will be within the community and get concerned    about what follows later, including the possible risks. By empowering farmers    in terms of knowledge and innovations leading to better production, the work    of extension workers can be improved. Roling (1995) explains that good farmers    generate good extension agents, in contrast to the common belief that good extensionists    produce good farmers, since the good farmers will always demanded for staff    that will deliver better services. It follows therefore, that an approach which    empowers farmers is likely to sustain a good and effective extension service.    He concludes that the best way to increase the effectiveness of the extension    service is not by giving staff more cars, training and so on but especially    increasing the countervailing power of farmers to influence and control field    extension workers.</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">The farmer-to-farmer    extension approach is based on two social theories, namely the 'Social Interaction'    Theory, specifically its 'Structural Function Model', and the 'Social Learning    Theory'. The first theory points to 'value consensus', which is the agreement    of community residents about their goals and the appropriate way of achieving    those goals (Hess, Markson and Stein 2000:16).</font></p>     ]]></body>
<body><![CDATA[<p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">The second theory    highlights the need for individuals to meet and discuss problems, identify solutions    and access mutual support from group members (Forsyth 2006:25). Use of community    facilitators based on the farmer-to-farmer model can be applied to the various    professions engaged in community development activities to boost the process.    Where professionals have had an involvement in projects, their attitudes towards,    and relationships with, members of the community, can demonstrate a radical    change: they testify to a deeper understanding of, and greater respect for community    perspectives - and a commitment to continue or upscale the process (Daniel,    Surridge and Thomas, 2003)</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2"><b>1.4 Role of    professionals in the farmer-to-farmer extension model</b></font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">The roles of the    professionals in the new model have included the following:</font></p>     <blockquote>        <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">a)&nbsp;Technical      training of the services providers</font></p>       <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">b)&nbsp;Participative      generation of the needed technologies</font></p>       <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">c)&nbsp;Institutional      building</font></p>       <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">d)&nbsp;Overall      policy formulation and implementation</font></p> </blockquote>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">Technical training    of the farmer-to-farmer extension model is provided by qualified professionals    through training of trainers. The process of identifying and selecting of the    trainees is facilitated by professionals. Here a multidisciplinary team of professionals    is involved since the training covers a wide range of courses.</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">Participative generation    of needed technologies is another crucial role of the professionals. Applied    research is carried out on identified topics in selected technology needs, by    qualified professionals.</font></p>     ]]></body>
<body><![CDATA[<p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">Community based    institutional building is facilitated by professionals who offer training on    leadership and organizational management. Such institutions are vital in sustaining    the services</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">Overall policy    formulation and implementation is carried out by the professionals. This covers    both administrative and technical policy aspects.</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2"><b>1.5</b>&nbsp;<b>Extension    services in Uganda</b></font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">For over a century,    public agricultural extension in Uganda has been offering the vital service    of advising and educating the farmers on agricultural productivity and production    (Opio-Odongo 2002; MAAIF, 1998).</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">In doing this the    public agriculture extension system has applied a number of models including</font></p>     <blockquote>        <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">(i)&nbsp;extension      by compulsion;</font></p>       <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">(ii)&nbsp;progressive      farmer-based extension;</font></p>       <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">(iii)&nbsp;education-led      extension;</font></p>       <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">(iv)&nbsp;extension      based on projects; and</font></p>       ]]></body>
<body><![CDATA[<p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">(v)&nbsp;the      unified extension strategy (Nalugooti 2005). Starting from 2000, the farmer-led,      privately delivered and public- funded advisory service was established under      the National Agricultural Advisory Services (NAADS) programme (MAAIF 2001).</font></p> </blockquote>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">Up to the 1980s,    public agricultural extension as an implementing agency of government policies    aimed at improving agricultural production and productivity, and enjoyed both    fiscal and political support. However, during the 1990s, the increasing costs    of running the public extension service and its failure to increase production    resulted in less fiscal and political support leading, to downsizing of its    staff. The total staff strength was reduced from 15000 down to 5000. The diminishing    role of the public extension service gave way to farmer-led extension services    promoted mainly by non-government organisations (NGOs) (Simpson and Owens, 2002).</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2"><b>1.6</b>&nbsp;<b>Farmer-led    extension services</b></font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">Farmer-to-farmer    extension proved to be very successful in Guatemala and the surrounding states    in South America. It is based on a paradigm shift aimed at targeting communities    instead of individuals' development. This is probably the most common form of    farmer-led extension service. The farmer extension facilitators (FEFs) are selected    from and vetted by the community. They receive comprehensive training from an    external agent in government or an NGO; they may receive remuneration from farmers    or an external agent for their work. In Uganda the farmer-to-farmer extension    is widely applied by NGOs and has been found effective in promoting sustainable    production. Kulika Charitable Trust Uganda (KCT), the Uganda Farmers Federation    (UNFFE) and the World Vision (WV) have adopted the approach across the country.    The farmer extension facilitators are comprehensively trained in production    technologies, sustainable production and value addition.</font></p>     <p>&nbsp;</p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="3"><b>2.</b>&nbsp;<b>STATEMENT    OF THE PROBLEM</b></font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">The declining role    of the public extension service created a delivery gap necessitating emergence    of new extension services providers (Rivera &amp; Amanor, 1991, Swanson &amp;    Samy, 2002). Swanson and Samy (2002) further explain that, with the decline    in government expenditures, public extension systems are not able to provide    adequate educational and technical extension programmes for all groups of farmers.    Furthermore, public extension has been less effective in responding to the basic    educational needs of small scale, marginal farmers due to insufficient resources    and the lack of a continuing flow of appropriate technology. Therefore, alternative    organisations, especially NGOs, have emerged to fill the gap in developing countries    Swanson and Samy (2002).</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">Many of the new    extension service providers, particularly NGOs, such as Kulika Charitable Trust    (KCT), the World Vision (WV), and Uganda National Farmers Federation (UNFFE),    employed the FFE model whose modes of operation and effectiveness were not well    understood. It is not clear to what extent the model has been successful and,    it is even less clear what factors have led to its perceived success. The study    was therefore designed to answer these and other related questions.</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">Key questions for    the study were: a) How are the major players characterised and how do they operate?    b) To what extent has the model resulted in more production and creation of    a multiplier effect? c) What are the factors that influence the effectiveness    of the approach? d) What are the farmers' perceptions of the approach?</font></p>     <p>&nbsp;</p>     ]]></body>
<body><![CDATA[<p><font face="Verdana, Arial, Helvetica, sans-serif" size="3"><b>3.</b>&nbsp;<b>OBJECTIVES    OF THE STUDY</b></font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">The objectives    of the study were to:</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">a)&nbsp;Identify    the key players in the farmer-to-farmer extension model</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">b)&nbsp;Explain    the nature and characteristics of the major players</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">c)&nbsp;Examine    the roles played by key players in the communities</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">d)&nbsp;Determine    appropriate communication channels in the communities; and,</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">e)&nbsp;Identify    the determinants of the effectiveness of the farmer-to-farmer extension model.</font></p>     <p>&nbsp;</p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="3"><b>4.</b>&nbsp;<b>THE    CONCEPTUAL FRAMEWORK FOR THE STUDY</b></font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">The conceptual    frame work (<a href="/img/revistas/sajae/v39n2/03f01.jpg">Figure 1</a>) was based on a four-factor    model including: a) the initial social economic status of the farmers; b) the    intervention of the farmer-to-farmer extension approach; c) the institutional    support by NGOs; and d) the farmers' institutional networks. It envisaged the    initial status of the farmers in terms of the social economic characteristics,    knowledge and skills; various interventions including the new extension approach,    the institutional frameworks which supported the interventions; the farmers'    social networks supporting communication and the subsequent outcomes, in terms    of increased farmer involvement and increased uptake of recommended technologies.    The framework also illustrated the independent variables consisting of the extension    approach, methods and techniques used. The farmers' social economic characteristics    such as age, education status, marital status, size of farms among others, also    form part of the independent variables. The dependent variables indicating the    effects arising from the extension efforts applied in the areas under study.    These include levels of participation, knowledge and skills, adoption of recommended    farming practices, non-traditional technologies adopted, productivity, levels    of income, and levels of food sufficiency. Effective use of the farmer-to-farmer    extension approach is to improve the levels of knowledge and skills and thereby    improve production.</font></p>     ]]></body>
<body><![CDATA[<p>&nbsp;</p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="3"><b>5. METHODS</b></font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2"><b>5.1</b>&nbsp;<b>Study    design</b></font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">The study adopted    a cross-sectional comparative survey design meant to collect perceptual data    on the effectiveness of the farmer-to-farmer extension approach in Uganda, as    practised by Kulika Charitable Trust (KCT), World Vision (WV), Masaka District    Farmers Association (MDFA), and Tororo District Farmers Association (TODFA).    Comparisons were made between levels of technology uptake and production before    and after application of the farmer-to-farmer extension by the farmer extension    facilitators (FEFs) and follower farmers (FFs). Also, comparisons were made    between the FEFs, FFs and the non-interventional farmers from areas where no    application of the farmer-to-farmer extension had taken place.</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2"><b>5.2</b>&nbsp;<b>The    information collected was in the following categories</b></font></p>     <blockquote>        <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">a)&nbsp;The characterisation      of the major players in the model including their age, sex, educational levels,      land owned, labour employed and the groups to which they belonged.</font></p>       <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">b)&nbsp;Data      on the uptake of selected technologies of major crops in the ecological zone      where the districts under study were located.</font></p>       <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">c)&nbsp;Information      on soil and water conservation and dairy cattle management as cross- cutting      activities in both Masaka and Tororo districts.</font></p>       <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">d)&nbsp;Data      on the indicators of success of the model including uptake, production and      food sufficiency.</font></p>       ]]></body>
<body><![CDATA[<p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">e)&nbsp;Data      on the activities of farmer extension facilitators.</font></p>       <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">f)&nbsp;Data      on the sources of information for the farmers.</font></p> </blockquote>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">The major methods    of primary data collection were the semi-structured questionnaires, which were    administered to the farmers, focus group discussions and key informant interviews.    Secondary data was collected from reports and libraries.</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2"><b>5.3 Sampling    frame</b></font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">The sampling frame    included follower farmers (FFs), who had benefited from the farmer-to-farmer    extension model as practised by the Kulika Charitable Trust, the World Vision    and the Uganda National Farmers Federation. Similarly, the farmer extension    facilitators formed another part of the sampling frame. Lists of FFs and FEFs    were compiled and random selection using a table of random numbers was applied    to the FFs but the FEF were purposively selected, to cover geographic spread.    The sampling frame for the control groups was two parishes from each of the    study district. The parishes were selected from areas that had not been involved    in NGO farmer-to-farmer model activities. In both cases farmers' nominal lists    were compiled and tables of random numbers were used to select respondents.</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">Geographical coverage    consisted of three sub-counties and eight parishes in Masaka district and nine    sub-counties and twenty five parishes in Tororo district. Both subcounties and    parishes were purposively selected to coincide with service delivery by all    the three NGOs.</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2"><b>5.4 Sample size</b></font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">The method of sample    proportions was applied in calculating the sample size, n (Cooper and Emory    1996).</font></p>     <p align="center"><img src="/img/revistas/sajae/v39n2/03x01.jpg"></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">where:</font></p>     ]]></body>
<body><![CDATA[<p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">n= Sample size</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">p = Proportion    of interest within the district (proportion of FFs in the two districts) <sup>q</sup>=    <sup>1-p</sup></font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">ó<sub>p</sub> =    sampling error =0.05/2.58 (precision divided by 90 % confidence that the proportion    lies within 2.58ó from the mean).</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">0.05 = precision    (chosen arbitrarily not to be confused with the level of significance).</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">Therefore, n =    (0.80 x 0.20) /&#91;0.05/2.58&#93; <sup>2</sup> +1 = 426</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">A sample size of    456 farmers was targeted for the study, and 30 farmers were added to compensate    for non-responses and refusals.</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2"><b>5.5 Sampling    procedure</b></font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">Farmer extension    facilitators FEFs were purposively selected for two major reasons:</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">i)&nbsp;they were    not demographically homogeneous and</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">ii)&nbsp;there    was need to cover adequate numbers of trained farmers by including more FEFs.    In Masaka district 24 FEFs were selected while in Tororo district 25 were selected.</font></p>     ]]></body>
<body><![CDATA[<p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">FFs were randomly    selected using a table of random numbers, from the list of all trained farmers    in purposively selected parishes where FEFs were deployed. Using the above procedure,    50 trained farmers were targeted from each organisation, making a total of 338    respondents for the two districts. One hundred and eighteen farmers were selected    from the non-intervention areas. In all, 456 respondents were interviewed.</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">Key informants    included the District Agricultural Officers of Masaka and Tororo districts;    Chief Administrative Officers; the head of World Vision Food Security Project;    the Chief Executive Officer in Kulika; The programme officer of World Vision;    the programme officer of the Uganda National Farmers Federation; the coordinators    of MADFA and TODFA.</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2"><b>5.6 Data analysis</b></font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">Quantitative data,    including comparison of the characteristics of the FEs and farmers FFs, the    association of independent and dependent variables, and the test for significance,    were analysed using STATA statistical package. Qualitative data was analysed    by summarising data under themes and sub themes and noting the significance    attached to and the emphasis put on the variables. Information on the institutional    framework was analysed according to the themes involved, including the administrative    and technical linkages between the existing government structures and the NGOs    set up. Much of the data concerning farmers included how the farmer extension    facilitators were selected, trained and deployed. The differences between the    methods used by the different organisations used to train farmer extension facilitators    were noted and contrasted. Data on the courses and curriculum were explained.    Observations of field activities and focus group discussion results were documented.</font></p>     <p>&nbsp;</p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="3"><b>6. RESULTS AND    DISCUSSIONS</b></font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2"><b>6.1</b>&nbsp;<b>Introduction</b></font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">This section presents    results and discussions of the study according to its objectives. The section    presents and discusses the identification and characterization of the major    players of the model, examines the role of the major players, shows the various    communication channels and brings out the determinants of the effectiveness    of the farmer-to-farmer extension model.</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2"><b>6.2</b>&nbsp;<b>Characteristics    and roles of key players</b></font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">In this part the    socio-economic characteristics of farmer extension facilitators and the follower    farmers are discussed.</font></p>     ]]></body>
<body><![CDATA[<p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">The results indicated    in <a href="/img/revistas/sajae/v39n2/03t01.jpg">Table 1</a>, show that the majority of farmer    extension facilitators and benefiting farmers were adults of mean age of 45    years; of approximately seven years of education on average; married; owned    small farms on which they used family labour mainly, with minimal hired labour.    The great majority held leadership positions in the communities including chairmanship    of farming groups, local councils, schools or churches. The leadership positions    they held and the interaction that followed ensured information-sharing at various    levels, which enhanced communication and discussion of issues concerning the    livelihoods of the residents. A large majority also had long experience in farming    spanning up to 30 years, and derived over 80 per cent of their income from farming.    All farmer extension facilitators were identified and vetted by their communities.    All received broad based training in subject matter, leadership and value chain    management. All were deployed in their own communities.</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">The socio-economic    characteristics of farmer extension facilitators and the follower farmers are    indicated in <a href="/img/revistas/sajae/v39n2/03t01.jpg">Tables 1</a> and <a href="/img/revistas/sajae/v39n2/03t02.jpg">2</a>    and the data shows that the majority of characteristics of the two groups are    closely similar.</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">Similar social    characteristics of benefiting farmers (<a href="/img/revistas/sajae/v39n2/03t02.jpg">Table 2</a>)    and farmer extension facilitators (<a href="/img/revistas/sajae/v39n2/03t01.jpg">Table 1</a>) leads    to the social closeness of members of the two groups. This enhances social interaction    and wide information-sharing between the members of the two groups. This contrasts    sharply with the public extension supervisors' criteria of putting emphasis    on theoretical knowledge and general lack of practical experience. In public    extension services the extension agents are not socially close to the beneficiaries    because of varying socio-economic characteristics.</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2"><b>6.3 Social closeness    or sharing similar socio-economic characteristics</b></font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">Social closeness    between farmer extension facilitators and those they trained was examined by    comparing the socio-economic characteristics. As indicated in <a href="/img/revistas/sajae/v39n2/03t03.jpg">Table    3</a>, the test for significance in the differences between the socio-economic    characteristics of both groups in the two districts under study did not show    any significant differences for most of the characteristics at p&lt;0.05. The    significant similarity of the socio-economic characteristics such as education,    size of labour, size of land, household assets, distances from markets, and    farming experiences supported findings of earlier studies, which revealed that    socio-economic similarities encourage more interaction (Bandiera &amp; Rasul    2005).</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">Socio-economic    closeness ensured sharing of information between farmer extension facilitators    and benefiting farmers thereby creating social interaction and promoting social    communication networks (Lunkuse 2004).</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2"><b>6.4 Community    information sources</b></font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">Social interaction    and communication between farmers and various information sources are indicated    in <a href="/img/revistas/sajae/v39n2/03t04.jpg">Table 4</a>. On average, farmers accessed information    more from farmer extension facilitators followed by radio farming programmes,    fellow farmers, NGOs and lastly the government extension agencies. The higher    contacts of farmer extension facilitators with benefiting farmers indicated    the emphasis that was placed on the intended role of the major players, the    farmer extension facilitators. The low interaction between farmers and the government    extension agent was due to lack of social and geographical closeness. Most government    workers are located far from the communities they serve, they are non-practitioners    and relatively younger than the    <br>   beneficiaries.</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2"><b>6.5 The multiplier    effect</b></font></p>     ]]></body>
<body><![CDATA[<p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">The study established    that a multiplier effect was created when follower farmers passed on the knowledge    and skills to fellow farmers in the community, as indicated in <a href="/img/revistas/sajae/v39n2/03t05.jpg">Table    5</a>, below. The number of secondary contacts made by follower farmers ranged    from 12 to 50 in both Masaka and Tororo districts. This means that each follower    farmer contacted between 12 and 50 other farmers and the process continued.    This was in line with earlier studies. Simpson and Owens (2002), in their study    in Ghana and Mali found that the farmer-to-farmer extension approach encourages    communication between farmers at several levels, thereby creating a multiplier    effect. Farmer estimates of the number of secondary contacts that they had made    outside their immediate family members ranged from ten to 20 and, in the case    of an active woman plantain farmer, over 100 such contacts.</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2"><b>6.6 Increased    technology uptake</b></font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">The effectiveness    of the farmer-to-farmer extension resulted into more adoption of technologies    and thus better production and increased food availability. <a href="#t6">Table    6</a> indicates the significance test between the number of technologies adopted    by the farmers who benefited from the farmer-to-farmer approach and those who    did not. In Masaka, out of the 32 technologies and practices promoted, 30 were    adopted by beneficiaries of the new extension approach giving 94 per cent, while    nonbeneficiaries adopted only 20 out of 32, which was 62 per cent. The same    trend was observed in Tororo district, where the adoption rate was 52 and 27    for beneficiaries and non-beneficiaries respectively.</font></p>     <p>&nbsp;</p>     <p><a name="t6"></a></p>     <p align="center"><img src="/img/revistas/sajae/v39n2/03t06.jpg"></p>     <p>&nbsp;</p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2"><b>6.7 Increased    food production</b></font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">Increased technology    adoption was followed by increased production and improved food availability    as indicated in <a href="#t7">Table 7</a> below. The same trend was recorded    in Tororo district.</font></p>     <p><a name="t7"></a></p>     ]]></body>
<body><![CDATA[<p>&nbsp;</p>     <p align="center"><img src="/img/revistas/sajae/v39n2/03t07.jpg"></p>     <p>&nbsp;</p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">The increase in    production was quite significant, as indicated in <a href="#t8">Table 8</a>    below. Two crops, namely banana and sweet potatoes, have been picked for this    purpose but the same happened for other enterprises.</font></p>     <p><a name="t8"></a></p>     <p>&nbsp;</p>     <p align="center"><img src="/img/revistas/sajae/v39n2/03t08.jpg"></p>     <p>&nbsp;</p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="3"><b>7.</b>&nbsp;<b>CONCLUSIONS</b></font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">The study revealed    that: a) the major players in the farmer-to-farmer extension were farmer extension    facilitators (FEF) b) the major players had similar socio-economic characteristics;    including age, years of schooling, sizes of farms and experiences in farming;    c) many key players had community roles, including farming and leadership that    enhanced social communication networks; d) information flow was more effective    among individuals of equal socio-economic status and engaged in similar socio-economic    activities; e) there was more interaction between farmers than between any other    individuals and extension agencies; f) farmer extension facilitators, the radio,    fellow farmers, NGOs and lastly the government agents were the main channels    of communication; g) measures of effectiveness included: i) increased uptake    of technologies; ii) increased food production and sales and iii) the multiplier    effect that ensured more information flow.</font></p>     ]]></body>
<body><![CDATA[<p>&nbsp;</p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="3"><b>8.</b>&nbsp;<b>RECOMMENDATIONS</b></font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">It was therefore    recommended that: a) selection of farmer extension facilitators should consider    social closeness as a criterion for identifying the correct individuals; b)    individuals with more community social roles should be considered for selection    as farmer extension facilitators since they have more chances of interacting    with the farmers; c) communities should be involved in the selection of farmer    extension facilitators to ensure accountability of the farmer extension facilitators;    d) to avoid social exclusion, farmer extension facilitators should be appropriately    trained to handle farmers of different social status. Where resource-poor small-scale    farmers were involved there may be a tendency to exclude the relatively large    farmers. However, the study revealed that farmer extension facilitators were    comprehensively trained and developed their model farms sufficiently to even    cater for the needs of the more progressive farmers in the communities</font></p>     <p>&nbsp;</p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="3"><b>REFERENCES</b></font></p>     <!-- ref --><p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">BANDIERA, O. 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M. 2002, <i>'Developing an Extension Partnership among Public,    Private, and Non-government Organizations'&#094;</i> Journal of International Agricultural    and Extension Education, Vol. 9 No.1.</font>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;[&#160;<a href="javascript:void(0);" onclick="javascript: window.open('/scielo.php?script=sci_nlinks&ref=571659&pid=S0301-603X201100020000300031&lng=','','width=640,height=500,resizable=yes,scrollbars=1,menubar=yes,');">Links</a>&#160;]<!-- end-ref --><!-- ref --><p><font face="Verdana, Arial, Helvetica, sans-serif" size="2"> VAN ZWANENBERG,    R. M. A. &amp; KING, A. 1975. <i>An Economic History of Kenya and Uganda,</i>    p.30, Kenya: East African Literature Bureau.</font>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;[&#160;<a href="javascript:void(0);" onclick="javascript: window.open('/scielo.php?script=sci_nlinks&ref=571660&pid=S0301-603X201100020000300032&lng=','','width=640,height=500,resizable=yes,scrollbars=1,menubar=yes,');">Links</a>&#160;]<!-- end-ref --><p>&nbsp;</p>     <p>&nbsp;</p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2"><b><a name="back"></a><a href="#top"><img src="/img/revistas/sajae/v39n2/seta.jpg" border="0"></a>    Corresponding author:    ]]></body>
<body><![CDATA[<br>   </b> Faculty of Applied Sciences,    <br>   Bishop Stuart University,    <br>   P O Box 9, Mbarara, Uganda.    <br>   E-mail: <u><a href="mailto:essemakula@agric.mak.ac.ug">essemakula@agric.mak.ac.ug</a></u>    or <u><a href="mailto:e.ssemakula@bsu.ac.ug">e.ssemakula@bsu.ac.ug</a></u>    <br>   Cell: 256-772476440 or 256-0777912012</font></p>      ]]></body>
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